Abstract Extreme Multi-label Text Classification (XMTC) is a key task of finding the most
relevant labels from a large label set for a document. Although some deep learning-based …

Recently, some existing feature selection approaches neglect the correlation among labels,
and almost manifold-based multilabel learning models do not considered the relationship …

The use of machine learning for the image classification process is growing all the time.
Many methods can be used to classify an image with good accuracy. Convolutional Neural …

Recently, with the growing popularity of micro-videos, multi-label learning has attracted
increasing attention due to its potential commercial value in different scenarios. However …

Incomplete multi-label learning is a challenging issue due to the difficulty of revealing low-
rank structure of multi-labels. There is already much literature to tackle the challenge by …

In multi-view multi-label learning (MVML), the data is described by multiple feature views
and annotated by a number of categorical labels. At present, most of the existing MVML …

Multi-label learning aims to solve classification problems where instances are associated
with a set of labels. In reality, it is generally easy to acquire unlabeled data but expensive or …

As one of the typical formats of prevalent user-generated content in social media platforms,
micro-videos inherently incorporate multimodal characteristics associated with a group of …

Currently, micro-videos have gained widespread acceptance as a prominent form of user-
generated content across various social media platforms. Accurate event analysis of micro …

Currently, there is a growing scholarly and industrial interest in micro-video-centric research.
Within these domains, multi-label learning has emerged as a fundamental yet attractive …